A Feasibility Study of Single-inhalation, Single-energy Xenon-enhanced CT for High-resolution Imaging of Regional Lung Ventilation in Humans

Pinkham, Daniel; Negahdar, Mohammadreza; Yamamoto, Tokihiro; Mittra, Erik; Diehn, Maximilian; Nair, Viswam S.; Keall, Paul J.; Maxim, Peter G.; Loo, Billy W.

doi:10.1016/j.acra.2018.03.006

Cited by 3 publications

(3 citation statements)

References 33 publications

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“…imaging and high-definition imaging in clinical application, can clearly show liver lesions and the anatomical relationship of surrounding tissues, providing the basis for formulating clinical treatment plans for patients (17)(18)(19).…”

Section: A B C Dmentioning

confidence: 99%

Comparative analysis of the efficacy and accuracy of magnetic resonance imaging (MRI) and contrast-enhanced CT for residual and new lesions after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer

Shao¹,

Wang²,

Yu³

et al. 2021

Transl Cancer Res TCR

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Background: The purpose of this study was to investigate the efficacy and accuracy of magnetic resonance imaging (MRI) and contrast-enhanced computed tomography (CECT) for residual and new lesions after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer (PHC).Methods: Seventy-two PHC patients admitted to Linyi Central Hospital from May 2018 to May 2020 were selected as the study subjects, with a total of 92 lesions. All patients were treated with TACE, and were followed up at 6 months postoperatively. In addition, all patients underwent digital subtraction angiography (DSA), and with DSA results serving as the gold standard for diagnosis, the efficacy and accuracy of MRI and CECT for residual and new lesions after TACE in PHC patients were evaluated.Results: There were no significant differences in the specificity between the two diagnostic methods (P>0.05), and the diagnostic accuracy and sensitivity of MRI were markedly higher than those of CECT (P<0.05). The number of residual and new lesions diagnosed by MRI was notably higher than that by multislice spiral computed tomography (MSCT) (P<0.05), and the detection rate of residual and new lesions after TACE in PHC patients with different types of iodized oil deposition by MRI was significantly higher than that by CECT (P<0.05). Also, the number of postoperative tumor capsules diagnosed by MRI was considerably higher than that by CECT (P<0.05). There were no significant differences between the two diagnostic methods in the score of residual enhancement appearances in the arterial phase after surgery (P>0.05). Furthermore, there were no notable differences between the two diagnostic methods in the diagnosis of portal vein tumorous emboli and the source of blood supply to lesions after surgery (P>0.05). Conclusions:The diagnostic accuracy and sensitivity of MRI for residual and new lesions after TACE in PHC patients were higher than those of CECT. However, these two diagnostic methods were similar in diagnosing portal vein tumorous emboli, the source of blood supply to lesions, and the score of residual enhancement appearances in the arterial phase after surgery.

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Section: A B C Dmentioning

confidence: 99%

Comparative analysis of the efficacy and accuracy of magnetic resonance imaging (MRI) and contrast-enhanced CT for residual and new lesions after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer

Shao¹,

Wang²,

Yu³

et al. 2021

Transl Cancer Res TCR

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“…An alternative CT-based ventilation imaging modality uses xenon-enhanced CT (XeCT), where a patient inhales an Xe-O 2 gas while undertaking a breath-hold CT (BHCT). 19 Conventional CTVIs rely on deformable image registration (DIR) to the inhalation and exhalation respiratory phases of a 4DCT then the application of a ventilation metric to estimate ventilation (in this paper, these will be referred to as "DIR-based"). The benefit of a CTVI is that the CT images are typically available from treatment planning, reducing the clinical time and monetary costs associated with nuclear medicine ventilation imaging.…”

Section: Introductionmentioning

confidence: 99%

“…CT ventilation imaging generally refers to when a treatment planning 4DCT is used to produce an estimation of ventilation within the lungs, thus producing a CTVI. An alternative CT‐based ventilation imaging modality uses xenon‐enhanced CT (XeCT), where a patient inhales an Xe–O 2 gas while undertaking a breath‐hold CT (BHCT) 19 . Conventional CTVIs rely on deformable image registration (DIR) to the inhalation and exhalation respiratory phases of a 4DCT then the application of a ventilation metric to estimate ventilation (in this paper, these will be referred to as “DIR‐based”).…”

Section: Introductionmentioning

confidence: 99%

Investigating the use of machine learning to generate ventilation images from CT scans

et al. 2022

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Background Radiotherapy treatment planning incorporating ventilation imaging can reduce the incidence of radiation‐induced lung injury. The gold‐standard of ventilation imaging, using nuclear medicine, has limitations with respect to availability and cost. Purpose An alternative type of ventilation imaging to nuclear medicine uses 4DCT (or breath‐hold CT [BHCT] pair) with deformable image registration (DIR) and a ventilation metric to produce a CT ventilation image (CTVI). The purpose of this study is to investigate the application of machine learning as an alternative to DIR‐based methods when producing CTVIs. Methods A patient dataset of 15 inhale and exhale BHCTs and Galligas PET ventilation images were used to train and test a 2D U‐Net style convolutional neural network. The neural network established relationships between axial input BHCT image pairs and axial labeled Galligas PET images and was evaluated using eightfold cross‐validation. Once trained, the neural network could produce a CTVI from an input BHCT image pair. The CTVIs produced by the neural network were qualitatively assessed visually and quantitatively compared to a Galligas PET ventilation image using a Spearman correlation and Dice similarity coefficient (DSC). The DSC measured the spatial overlap between three segmented equal lung volumes by ventilation (high, medium, and low functioning lung [LFL]). Results The mean Spearman correlation between the CTVIs and the Galligas PET ventilation images was 0.58 ± 0.14. The mean DSC over high, medium, and LFL between the CTVIs and Galligas PET ventilation images was 0.55 ± 0.06. Visually, a systematic overprediction of ventilation within the lung was observed in the CTVIs with respect to the Galligas PET ventilation images, with jagged regions of ventilation in the sagittal and coronal planes. Conclusions A convolutional neural network was developed that could produce a CTVI from a BHCT image pair, which was then compared with a Galligas PET ventilation image. The performance of this machine learning method was comparable to previous benchmark studies investigating a DIR‐based CTVI, warranting future development, and investigation of applying machine learning to a CTVI.

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Incorporation of Functional Lung Imaging Into Radiation Therapy Planning in Patients With Lung Cancer: A Systematic Review and Meta-Analysis

Midroni,

Salunkhe,

Liu

et al. 2024

International Journal of Radiation Oncology*Biology*Physics

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A Feasibility Study of Single-inhalation, Single-energy Xenon-enhanced CT for High-resolution Imaging of Regional Lung Ventilation in Humans

Cited by 3 publications

References 33 publications

Comparative analysis of the efficacy and accuracy of magnetic resonance imaging (MRI) and contrast-enhanced CT for residual and new lesions after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer

Comparative analysis of the efficacy and accuracy of magnetic resonance imaging (MRI) and contrast-enhanced CT for residual and new lesions after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer

Investigating the use of machine learning to generate ventilation images from CT scans

Incorporation of Functional Lung Imaging Into Radiation Therapy Planning in Patients With Lung Cancer: A Systematic Review and Meta-Analysis

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